MINDFULNESS AND NUTRITION AND EXERCISE BEHAVIORS IN COLLEGE STUDENTS: THE MODERATING ROLE OF SLEEP QUALITY
A DISSERTATION IN Counseling Psychology
Presented to the Faculty of the University of Missouri-Kansas City in partial fulfillment of
the requirements for the degree DOCTOR OF PHILOSOPHY
by
TARYN ACOSTA LENTZ
M.A., University of Missouri-Kansas City, 2011 B.F.A., Cornell University, 2006
Kansas City, Missouri 2014
© 2014
TARYN ACOSTA LENTZ ALL RIGHTS RESERVED
MINDFULNESS AND NUTRITION AND EXERCISE BEHAVIORS IN COLLEGE STUDENTS: THE MODERATING ROLE OF SLEEP QUALITY
Taryn Acosta Lentz, Candidate for the Doctor of Philosophy University of Missouri-Kansas City, 2014
ABSTRACT
Inadequate nutrition, physical inactivity, and poor sleep quality have become increasingly common in college student populations, placing students at greater risk of being
overweight or obese in adulthood. Researchers have adopted the construct of
mindfulness to better understand and potentially modify health behavior. The purpose of the present investigation was to examine the relationships between mindfulness and health behaviors (i.e., nutrition and exercise) in undergraduate college students. Sleep quality was tested as a moderator of these relationships. The current study also explored the unique influence of each of the five facets of mindfulness (i.e., observing, describing, acting with awareness, nonreactivity to inner experience, and nonjudging of inner
experience) on college students’ nutrition and exercise behavior. The sample consisted of 357 undergraduates from colleges throughout the United States who completed online surveys. Hierarchical multiple regression analyses demonstrated that sleep quality moderated the relationship between mindfulness and nutrition behavior with an enhancing effect. However, moderating effects for the mindfulness-exercise behavior relationship did not hold. Hierarchical multiple regression analyses also revealed the Observe facet of mindfulness to be most predictive of nutrition behavior, whereas the Observe and Describe facets were most predictive of exercise behavior. The present
findings highlight that enhancing mindfulness and improving sleep hygiene may be particularly beneficial in elevating health-promoting behavior in undergraduate college students. Limitations, future directions, and implications are discussed.
APPROVAL PAGE
The faculty listed below, appointed by the Dean of the School of Education, have examined a dissertation titled “Mindfulness and Nutrition and Exercise Behaviors in College Students: The Moderating Role of Sleep Quality,” presented by Taryn Acosta Lentz, candidate for the Doctor of Philosophy degree, and certify that in their opinion it is worthy of acceptance.
Supervisory Committee
Chris Brown, Ph.D., Committee Chair Counseling and Educational Psychology
Jacob Marszalek, Ph.D.
Counseling and Educational Psychology Nancy Murdock, Ph.D.
Counseling and Educational Psychology Johanna Nilsson, Ph.D.
Counseling and Educational Psychology LaVerne Berkel, Ph.D.
CONTENTS ABSTRACT ... iii ILLUSTRATIONS ... ix LIST OF TABLES ...x ACKNOWLEDGMENTS ... xi Chapter 1. INTRODUCTION ...1 Purpose ...6
2. REVIEW OF THE LITERATURE ...7
Health Risk Behaviors in College Students ...7
Nutrition and Exercise ...7
Sleep ... 13
Sleep, Nutrition, and Exercise ... 17
Mindfulness... 20
Definition of Mindfulness ... 20
Theory of Mindfulness ... 21
Attention and Awareness ... 21
Acceptance ... 22
Mindfulness, Nutrition, and Exercise ... 22
Rationale and Purpose... 26
Hypotheses and Research Questions ... 27
3. METHODOLOGY ... 31
Measures ... 34
Five Facet Mindfulness Questionnaire (FFMQ) ... 34
Health-Promoting Lifestyles Profile-II (HPLP-II) ... 36
Sleep Quality Index (SQI) ... 38
Perceived Stress Scale (PSS) ... 39
Demographic Questionnaire ... 39 Procedure ... 40 4. RESULTS ... 42 Data Examination... 42 Main Analyses ... 46 Hypotheses Testing ... 46 Research Questions ... 53 5. DISCUSSION ... 56 Hypothesis 1... 56 Hypothesis 2... 58 Research Question 1 ... 59 Research Question 2 ... 61
Limitations and Future Directions ... 62
Implications... 65
Appendix A. FIVE FACET MINDFULNESS QUESTIONNAIRE ... 68
B. HEALTH PROMOTION LIFESTYLE PROFILE-II – NUTRITION ... 71 C. HEALTH PROMOTION LIFESTYLE PROFILE-II – PHYSICAL ACTIVITY. 73
D. SLEEP QUALITY INDEX ... 75
E. PERCEIVED STRESS SCALE ... 77
F. DEMOGRAPHIC QUESTIONNAIRE ... 79
G. IRB APPROVAL ... 82
H. SOLICITATION EMAIL FOR STUDENT AFFAIRS COORDINATORS ... 84
I. SOLICITATION EMAIL FOR PARTICIPANTS ... 86
J. COVER LETTER ACCOMPANYING ONLINE SURVEY ... 88
K. ONLINE INCENTIVE FORM ... 90
REFERENCE LIST ... 92
ILLUSTRATIONS
Table Page
1. Model of Hypothesis 1 ...29
2. Model of Hypothesis 2 ...29
3. Model of Research Question 1 ...30
4. Model of Research Question 2 ...30
5. The Relationship Between Mindfulness (total score) and Nutrition Behavior as a Function of Sleep Quality ...49
TABLES
Table Page
1. Summary of Demographic Characteristics for the Total Sample ...33
2. Means, Standard Deviations, Reliability, Ranges, Skewness, and Kurtosis Statistics of Study Measures and A Priori Variables ...43
3. Intercorrelations among Control, Predictor, and Criterion Variables ...44
4. Collinearity Statistics for Predictors of Nutrition Behavior ...45
5. Collinearity Statistics for Predictors of Exercise Behavior ...45
6. Summary of Hierarchical Multiple Regression Analysis for Variables Predicting Nutrition Behavior ...48
7. Summary of Hierarchical Multiple Regression Analysis for Variables Predicting Exercise Behavior ...50
8. Summary of Exploratory Hierarchical Multiple Regression Analysis for Variables Predicting Nutrition Behavior ...51
9. Summary of Exploratory Hierarchical Multiple Regression Analysis for Variables Predicting Exercise Behavior ...52
10. Summary of Hierarchical Multiple Regression Analysis Predicting Nutrition Behavior from the Five Facets of Mindfulness ...53
11. Summary of Hierarchical Multiple Regression Analysis Predicting Nutrition Behavior from the Five Facets of Mindfulness ...54
ACKNOWLEDGEMENTS
I want to express my deepest gratitude to Dr. Chris Brown, my committee chair and advisor, for her exceptional leadership, as she conveys a sincere passion for research and scholarship. She serves a model of the type of counseling psychologist I aspire to be and I am thankful for her contribution to my professional future. Without her thoughtful guidance and support, this dissertation would not have been possible.
A special thanks to my committee members, Drs. Johanna Nilsson, Nancy Murdock, LaVerne Berkel, and Jake Marszalek, who have all been instrumental in my professional development and whose time and energy is genuinely appreciated. I am so privileged to learn from these talented individuals and benefit from their wisdom.
I would also like to thank my parents, to whom I am indebted for their countless sacrifices that made my educational goals attainable. I am grateful they instilled in me the ability to dream fearlessly and tirelessly pursue my ambitions. To my siblings, Taylor and Dax, who helped me put things in perspective and sent me electronic Starbucks gift cards when I needed them most. Their many accomplishments within the fields of art history and hospitality have inspired me to persist in the face of adversity. A special thanks to my cat, Frida, for encouraging me to take breaks by sitting on my keyboard.
Finally, I would like to express my appreciation to my husband and best friend, Patrick. I would never have been able to complete my dissertation without his love, humor, and encouragement. I am excited to share this great accomplishment with him.
CHAPTER 1 INTRODUCTION
Obesity has been recognized as the public health challenge of our time.
According to the American College Health Association (ACHA, 2008), 36.7% of college students are either overweight (body mass index [BMI] 25.0 – 29.9 kg/m2) or obese (BMI ≥ 30.0 kg/m2). Excess weight is considered a key source of premature mortality and morbidity, and has been found to be associated to a variety of health complications, including cardiovascular diseases, type 2 diabetes, hypertension, dyslipidemia, and stroke (Brancati, Kao, Folsom, Watson, & Szklo, 2000; Flegal, Carroll, Ogden, & Johnson, 2002; Mokdad, Bowman, Ford, Vinicor, Marks, & Koplan, 2000). Given that weight problems in late adolescence are highly predicative of overweight and obesity in
adulthood (Guo, Wu, Chumela, & Roche, 2002), unhealthy dietary behavior and physical inactivity have been identified as two of the top six health risk behaviors in college students (e.g., Douglas, Collins, Warren, Kann, Gold, & Clayton et al., 1997; Lowry, Galuska, Fulton, Wechsler, Kann, & Collins, 2000). Further, a growing body of evidence has identified sleep deprivation as another important risk factor for overweight and obesity (Patel & Hu, 2008; Van Cauter & Knutson, 2008).
The transition from high school to college is marked by drastic environmental changes, which likely influence health related behaviors (Crombie, Dutton, Panton, & Abood, 2009; Lenz, 2001). Much empirical attention has been devoted to documenting unhealthy behaviors in college students, specifically inadequate nutrition, physical inactivity, and sleep deprivation (e.g., Anding, Suminski, & Boss, 2001; Haberman & Luffey, 1998). For example, research has found that the majority of college students
typically consume a diet that is low in fruits and vegetables, while high in sugar, sodium, and fat (Anding et al., 2001; Hendricks, Herbold, & Fung, 2004; Lowry et al., 2000; Schutte, Song, & Hoerr, 1996). Other problematic dietary behaviors identified in college student populations include: frequent meal skipping (Debate, Topping, & Sargent, 2001; Sax, 1997), limited food variety (Shutte et al., 1996), frequent snacking on energy-dense foods, and high levels of fast food consumption (Task Force on National Health
Objectives for Higher Education, 1991). Empirical data demonstrate that physical
activity levels decline dramatically from junior high school to college graduation (Anding et al., 2001), and several researchers have reported that college students tend to lead relatively sedentary lifestyles (e.g., Anding et al., 2001; Kelley & Kelley, 1994; Pinto & Marcus, 1995). According to the National College Health Assessment (NCHA; 2012), roughly 50% of undergraduates fail to meet the current federal guidelines for aerobic and muscle strengthening physical activity (ACHA, 2012). Furthermore, empirical research has shown that only 11% of undergraduate college students reported good sleep hygiene (Buboltz, Brown, & Soper, 2001). In fact, Forquer, Camden, Gabriau, and Johnson (2008) found that over one-third of college students reported taking longer than 30 minutes to fall asleep, waking up more than once per night, and feeling fatigued during the day. Despite the established risks, it is evident that inadequate nutrition, physical inactivity, and sleep deprivation have become increasingly common in college student populations.
Recently, researchers have adopted the construct of “mindfulness” to better understand and potentially modify health behavior. Mindfulness is an Eastern concept originating in the Buddhist spiritual tradition, which has only recently come into
prominence within contemporary Western society. Simply defined, mindfulness refers to the “nonelaborative awareness to current experience” with an attitude of “curiosity, experiential openness, and acceptance” (Bishop, Lau, Shapiro, Carlson, Anderson, & Carmody et al., 2004, p. 234). Although mindfulness may be cultivated with the regular practice of meditation, Kabat-Zinn (2003) highlighted that mindfulness is an inherent human capacity, as everyone is mindful from moment to moment to one degree or another. Thus, in addition to being a state of consciousness, researchers have proposed that mindfulness may also be considered a trait, in that some individuals are typically more mindful than others (Brown & Ryan, 2003; Thompson & Waltz, 2007).
While some researchers argue that dispositional mindfulness has a single factor structure (e.g., Brown & Ryan, 2003), others conceptualize dispositional mindfulness as a multidimensional construct. For example, Baer, Smith, Hopkins, Krietemeyer, and Toney (2006) utilized factor analysis to identify five facets of mindfulness: observing, describing, acting with awareness, nonreactivity to inner experience, and nonjudging of inner experience. The Observing factor includes noticing internal and external
experiences (e.g., sensations, thoughts, emotions, sights, and sounds). The Describing factor involves using language to label and prescribe meaning to internal experiences. The Acting with awareness factor is the tendency to focus attention on present moment activities, as opposed to behaving mechanically (i.e., being on automatic pilot). The Nonreacting to inner experience factor refers to allowing thoughts and feelings to come and go, without elaboration. The Nonjudging of inner experience factor involves adopting a nonevaluative orientation toward thoughts and feelings. For the purposes of the present investigation, mindfulness was assessed as a multidimensional construct.
Over the past few decades, the psychological and physical health benefits of mindfulness have generated considerable interest. In the context of dietary behavior, the findings have been promising and indicate an inverse relationship between mindfulness and disordered eating behavior. More specifically, mindfulness-based interventions have been found to diminish food cravings (Alberts, Mulkens, Smeets, & Thwissen, 2010), decrease binge eating (Kristeller & Hallet, 1999), and reduce BMI in overweight individuals (Tapper, Shaw, Ilsley, Hill, Bond, & Moore, 2009). Although the health behavior literature is dominated by studies that explore the relationship between
mindfulness and disordered eating, recent findings suggest a positive association between mindfulness and nutrition behavior (e.g., fruit and vegetable intake; Gilbert & Waltz, 2010; Grinnell, Greene, Melanson, Blissmer, & Lofgren, 2011). In regards to exercise behavior, some investigations have detected increases in physical activity following mindfulness-based interventions, even when physical activity was not the target of the intervention (e.g., Carlson, Speca, Patel, & Goodey, 2004). However, correlational studies examining the relationship between mindfulness and exercise behavior have yielded mixed findings and warrant further investigation (e.g., Murphy, Mermelstein, Edwards, & Gidycz, 2012; Roberts & Danoff-Burg, 2010). In the context of sleep hygiene, empirical research has shown that mindfulness practice may help reduce sleep disturbances that are related to stress (Carlson & Garland, 2005), and improve overall sleep quality in novice meditators (Brand, Holsboer-Trachsler, Naranjo, & Schmidt, 2012). Descriptive studies have found that college students with greater levels of
dispositional mindfulness tend to report better sleep quality (Murphy et al., 2012; Roberts & Danoff-Burg, 2010).
College students’ sleep habits and consequent sleep quality can have profound physiological and behavioral consequences (Buboltz et al., 2001; National Sleep
Foundation, 2008). Previous literature reviews and meta-analyses have found significant associations between sleep duration and obesity, however researchers are only beginning to understand the mechanisms involved. Across studies, findings indicate an inverse relationship between sleep quality and appetite. Experimental evidence suggests that sleep deprivation may alter the secretory patterns of two appetite-regulating hormones, ghrelin and leptin (Banks & Dinges, 2007; Spiegel, Tasali, Penev, & Van Cauter, 2004). In studies of young healthy men, sleep curtailment was associated with elevated ghrelin and suppressed leptin secretion, and corresponded to increased hunger and appetite (Brondel, Romer, Nouges, Touyarou, & Davenne, 2010; Spiegel et al., 2004). Sleep deprivation may also affect nutritional choices, as sleep restriction is strongly correlated with increased caloric consumption of snacks prior to bedtime (Nedeltcheva, Kilkus, Imperial, Kasza, Schoeller, & Penev, 2009). In a rural Midwestern sample, Stamatakis and Brownson (2007) found that individuals who slept less than 7 hours consumed more fast food and high-fat food than those who slept 7-8 hours per night. Spiegel and
colleagues (2004) observed a 33-45% increase in craving for carbohydrate-rich foods as a result of sleep restriction. Low sleep duration has also been associated with fatigue (Caldwell, 2002; Forquer et al., 2008) and reduced physical activity (Patel, Malhotra, White, Gottlieb, White, & Hu, 2006). Schmid, Hallschmid, Lassen, Mahnke, Schultes, and Schiöth et al. (2009) confirmed that sleep loss led to decreased physical activity levels among young healthy men. In a recent study, Bromley, Booth, Kilkus, Imperial, and Penev (2012) found that sleep restriction resulted in reduced amount and intensity of
physical activity in adults at risk for type 2 diabetes. Given the identified health consequences of insufficient sleep, the present study examined the influence of sleep quality in the relationship between mindfulness and health behavior (i.e., nutrition and exercise).
Purpose
Despite the established risks of being overweight or obese, college students continue to engage in adverse health related behaviors at relatively high rates. That is, college students’ lives are plagued by inadequate nutrition (Lowry et al., 2000), physical inactivity (Anding et al., 2001), and poor sleep quality (Buboltz et al., 2001). Although there is a growing body of evidence linking mindfulness and sleep quality, no study has examined the role of sleep quality in the relationships between mindfulness and nutrition, and mindfulness and exercise behavior. Given the physiological consequences of sleep deprivation, one may speculate whether even a mindful person can successfully
implement good nutrition and exercise habits when they suffer from poor sleep hygiene. Thus, the present study was designed to explore the relationships between mindfulness and health behaviors in college students; in particular, nutrition, exercise, and sleep. More specifically, the present study explored the potential moderating role of sleep quality in the relationships between mindfulness and nutrition, and mindfulness and exercise behavior. Further, the current investigation examined the influence of each of the five facets of mindfulness (observing, describing, acting with awareness,
nonreactivity to inner experience, and nonjudging of inner experience) on undergraduate college students’ nutrition and exercise behavior.
CHAPTER 2
REVIEW OF THE LITERATURE Health Risk Behaviors in College Students
Nutrition and exercise behavior are key determinants of health status, and are associated with 4 of the 10 leading causes of death in the United States (US Department of Health and Human Services [HHS], 2000). Sleep is also imperative for overall health, as complex neurological, physiological, and hormonal processes occur during sleep (Dement, 2000). Research has shown that a healthy diet, regular physical activity, and good sleep hygiene are independently associated with a reduced risk for obesity, coronary heart disease, stroke, hypertension, and type 2 diabetes (Ayas, White, Manson, Stampfer, Speizer, & Malhotra et al., 2003; Beihl, Liese, & Haffner, 2009; Gangwisch, Heymsfield, Boden-Albala, Buijs, Kreier, & Pickering et al., 2006; Hasler, Buysse, Klaghofer,
Gamma, Ajdacic, & Eich et al., 2004). However, the majority of college students fail to meet the nutrition and exercise guidelines necessary for health benefits (ACHA, 2012), typically consuming diets high in fat, sodium, and sugar while leading relatively sedentary lifestyles (Anding et al., 2001; Pinto & Marcus, 1995). In addition, sleep deprivation and poor sleep quality are highly prevalent on college campuses, as research has shown that college students report at least twice as many sleep problems as the general population (Brown, Soper, & Buboltz; 2001). To better our understanding of the health risk behaviors in college students, the following review of the literature will examine the nutrition, exercise, and sleep habits of undergraduates.
Nutrition and Exercise
negative changes can occur in health behaviors, particularly nutrition and exercise (Douglas et al., 1997; Lowry et al., 2000). In 2001, Anding and colleges examined the dietary and exercise behaviors of 60 female college students in the context of the Dietary Guidelines for Americans (HHS, 1995). The dietary guidelines outlined the following 7 recommendations: (a) eat a variety of foods; (b) balance the food you eat with physical activity; (c) choose a diet with plenty of fruits, vegetables, and grain products; (d) choose a diet low in fat, saturated fat, and cholesterol, (e) choose a diet moderate in sugars; (f) choose a diet moderate in salt and sodium; and (g) drink alcoholic beverages in
moderation. Participants completed an assessment of their physical activity engagement over the past month, and were asked to record their food consumption for 3 days. Mean BMI levels were indicative of healthy weights, however, 25% of the sample was
classified as overweight. Although participants met the daily recommended servings for meat, the majority failed to consume enough fruits, vegetables, grains, or dairy products. In fact, only 15% of participants reported consuming 5 or more servings of fruits and vegetables daily. Further, most participants exceeded suggested levels of saturated fat, sugar, and sodium. In regards to physical activity, approximately 25% of participants surveyed reported that they exercised regularly. Although most participants followed at least one of the dietary guidelines, no participant adhered to all seven recommendations. The findings of this study are consistent with those of previous investigations in that a large majority of the sample did not consume the recommended servings of food groups nor did they engage in regular physical activity (Dinger & Waigandt, 1997; Haberman & Luffey, 1998; Schutte et al., 1996).
shown reduced energy intake to be more effective for weight loss as compared to physical activity (Votruba, Horvitz, & Schoeller, 2000). In a study of 630 male and female college students, Debate and colleagues (2001) explored students’ current weight status, dietary practices, and dietary patterns. Participants completed a questionnaire that assessed dietary and weight-control behaviors, and were asked to report their food
consumption over the past 24 hours by using the groups identified by the Food Guide Pyramid (United States Department of Agriculture [USDA], 1992). Of the sample, 64% of the students had healthy BMI levels. Similar to Anding et al. (2001), results indicate that the majority of college students did not meet the daily recommended food servings as described by the Food Guide Pyramid. More specifically, only 18% of participants consumed 5 servings of fruit and vegetables per day, 7% consumed 6 or more servings of grain, and 53% consumed 2 or more servings of dairy. These findings are comparable to the results of the National College Health Risk Behavior Survey, which found that 75% of participants failed to consume a total of 5 fruits and vegetables per day (CDC, 1997). Consistent with other studies on college meal skipping (e.g., Huang, Song, Schemmel, & Hoerr, 1994; Hertzler & Frary, 1989), breakfast was never/rarely consumed by 44% of participants. In addition, approximately 32% of students reported eating fast food
always/often. These findings support Sneed and Holdt (1991) who indicated that college women and men consume approximately 2 fast food meals per week.
In 2003, Huang, Harris, Lee, Nazir, Born, and Kaur surveyed 736 college students to assess weight, diet, and physical activity. Participants responded to questionnaire items regarding their dietary and exercise habits. According to participants’ BMI levels, roughly 21% were overweight and 4% were obese. Of note, men were more likely than
women to be overweight, but not obese. In regards to nutrition, 69% of participants consumed fewer than 5 servings of fruit and vegetables per day, and 67% consumed less than 20g of fiber. Women consumed significantly less fiber than their male counterparts. Exercise levels were also low, as physical activity guidelines recommend that adults do at least 30 minutes of aerobic exercise each day (United States Department of Health and Human Services [HHS], 2008). Men were more likely to engage in aerobic exercise, and reported exercising more days per week than women. Overall, participants reported engaging in aerobic exercise an average of only 2.8 days per week, and doing strength training exercises 2.2 days per week. In addition, 16% of students reported engaging in no physical activity. Another study involving undergraduate students revealed that 59% of participants exercised 3 or more times per week, and 30% did not engage in exercise at all (Racette, Deusinger, Strube, Highstein, & Deusinger, 2005). Collectively, these findings are consistent with those of Pinto and Marcus (1995), who concluded that a substantial portion of college students lead rather sedentary lifestyles.
In a longitudinal study, Butler, Black, Blue, and Gretebeck (2004) sought to address the dietary, physical activity, and body weight parameter changes associated with relocation from home to college. Of the 54 first-year college women sampled,
approximately 15% were overweight and 5% were obese. Similar to previous
investigations, the data revealed that roughly 80% of the participants did not meet the minimum recommendations for fruits, vegetables, grains, or dairy (Haberman & Luffey, 1998). Interestingly, the researchers found a significant caloric decrease over the course of 5 months, but observed a significant increase in body weight parameters during the same period. Butler and colleagues (2004) attributed body weight changes to a
significant decline in physical activity. Not to mention, fat mass increased, which
indicate a reduction in physical fitness that is likely associated with a lack of exercise. In contrast to previous assumptions (Votruba et al., 2000), the findings suggest that physical activity patterns may be a stronger indicator of weight gain than dietary intake.
Although many people have embarked on ambitious exercise programs at one time or another, most struggle to maintain a regular exercise regimen. In fact, empirical research has estimated that 50% of individuals who begin an exercise program drop out within the first 6 months, or fail to maintain physical activity at the intended level (e.g., Dishman, 1988; Marcus, Bock, & Pinto, 1997). In a sample of 392 Canadian university students, Irwin (2007) conducted a longitudinal investigation to identify the extent to which college students maintain physical activity at a level necessary for health promotion over a 1-month period. Participants responded to items regarding the frequency and intensity of their physical activity experiences, and were asked to keep a physical activity log. Of the respondents, only 35% of students maintained physical activity for 1 month at the level necessary to gain health benefits. No gender differences were found. This prevalence rate is similar to the findings of a cross-sectional study by Sarkin, Nichols, Sallis, and Calfas (1998), who identified that roughly 37% of college students were sufficiently physically active for health benefits.
In a recent longitudinal investigation, Wengreen and Moncur (2009) examined changes in weight, dietary intake, and physical activity in 159 first-year college students. Participants completed surveys regarding their dietary intake and physical activity over the past six months of high school and during their first semester at college. At the start of the investigation, 14% of participants were overweight and 6% were obese. Over the
course of the study, weight and BMI levels increased. Specifically, 23% of participants gained ≥ 5% of their body weight, yet no participants lost ≥ 5% of their body weight during the same period. Among those who gained ≥ 5% of their body weight, the average amount of weight gained was 4.5 kg (9.9 lbs.). There was no significant difference in the amount of weight gained by men and women. Findings indicate that college students who gained ≥ 5% of their body weight were more likely to eat breakfast, and participated in less physical activity. The association between breakfast consumption and weight gain is surprising, as previous research has provided evidence that breakfast skipping is positively correlated with body weight (e.g., Rampersaud, Pereira, Girard, Adams, & Metzl, 2005). The authors suggested that the observed findings regarding breakfast consumption may be attributed to eating in all-you-can-eat dining facilities. In fact, those participants who gained ≥ 5% of their body weight consumed an average of 2.1 more meals per week in campus dining facilities than participants who did not gain a significant amount of weight. Similarly, other researchers have found college weight gain to be highly correlated with eating breakfast and lunch in all-you-can-eat dining halls (Levitsky, Halbmaier, & Mrdjenovic, 2004). Levitsky et al. (2004) hypothesized that campus dining facilities offer a great abundance and variety of food, which may promote excess energy intake. In regards to physical activity, the results are consistent with the findings of Butler et al. (2004) and Jung, Bray, and Martin Ginis (2008) who also found a significant association between weight gain and decreases in physical activity, despite overall reductions in energy intake. Given that 79% of students who gained ≥ 5% of their body weight lived on campus, the findings are interesting to compare to those of Bray, Millen, and Kwan (2004) who found that students who move
away from their parents’ home to an on-campus residence showed decreased levels of physical activity during their first year of college, whereas students who lived at home showed no such decline.
In sum, numerous researchers have reported that college students display poor nutrition and exercise behavior. The typical diet of college students is often low in fruits and vegetables and high in fat, sugar, and sodium (Anding et al., 2001; CDC, 1995; Debate et al., 2001), which may be characterized as a diet deficient in essential vitamins and minerals (Hendricks et al., 1998; Zive, Nicklas, Busch, Myers, & Berenson, 1996). Although all-you-can-eat dining halls offer a vast array of foods, college students fail to eat a great enough variety of foods to meet the minimum recommendations outlined by the Food Guide Pyramid (Anding et al., 2001; Debate et al., 2001). College students also engage in frequent meal skipping (Debate et al., 2001; Huang et al., 1994; Hertzler & Frary, 1989) and have high levels of fast food consumption (Debate et al., 2001; Sneed & Holdt, 1991). In regards to exercise, the majority of college students are not sufficiently physically active for health benefits (Irwin, 2007; Sarkin et al., 1998). Evidence indicates that as students transition from high school to college, physical activity levels decline (Butler et al., 2004; Jung et al., 2008; Bray et al., 2004; Wengreen & Moncur, 2009), resulting in a considerable body of students leading inactive lifestyles (Pinto & Marcus, 1995).
Sleep
The quantity and quality of sleep among college students have changed dramatically over the past several decades. Hicks, Fernandez, and Pellegrini (2001a) conducted a longitudinal investigation, sampling 3 large cohorts of college students over
three consecutive decades. In the late 1970s, a sample of 1,839 students slept an average of 7.3 hours, whereas a similar sample of college students surveyed a decade later
reported that they slept an average of 6.87 hours per night (Hicks, Mistry, Lucero, Marcial, & Pellegrini, 1990). Between 1970 and 2001, the median sleep duration of college students dropped 1 hour, from 7.75 to 6.65 hours per night (Hicks et al., 2001a), which is far below the recommended 8.5 to 9.25 hours for their age group (National Sleep Foundation, 2008). However, subsequent reports regarding average sleep duration in college students have been inconsistent. Hoesk, Phelps, and Jensen (2004) sampled 996 students and found a mean sleep duration of 7.69 hours per night. In a sample of 313 college students, Forquer et al. (2008) reported a mean sleep duration of 7.2 on weekdays and 8.6 hours on weekends. Interestingly, researchers have observed that college
students often deprive themselves of sleep during the week and attempt to “catch up” on sleep during the weekends (Brown et al., 2001; Jensen, 2003). College students also frequently shift their bedtime and wake time (Tsia & Li, 2004), despite evidence that optimal healthy sleep is best achieved by maintaining a consistent sleep/wake schedule. It appears that as students transition to college, their sleep habits tend to change and usually not for the better (Pilchner, Ginter, & Sadowsky, 1997).
More recently, Liguori, Schuna, and Mozumdar (2011) conducted a longitudinal study that assessed changes in sleep duration over the course of the semester in a sample of 820 male and female undergraduates. Participants completed surveys inquiring about their sleep habits, perceptions, and disturbances. Sleep duration ranged from 7.30 to 7.58 hours per night, with first-year students sleeping 20 minutes longer than upper division students. Mean sleep duration in this study was longer than values reported in previous
investigations (Hicks et al., 2001a; Forquer et al., 2008, Hoesk et al., 2004), and even increased over the course of the semester. Interestingly, female students had a significant increase of about 30 minutes in mean sleep duration throughout the semester, which occurred mostly during the winter months. Although sleep quantity was adequate,
participants reported a mean of only 3.39 days per week where they awoke feeling rested. Comparably, data from the NCHA (2012) indicated that only 10% of college students report getting enough sleep to feel rested 6 out of 7 days of the week (ACHA, 2012).
In addition to sleep duration, college students’ sleep quality has received increased and warranted empirical attention. Evidence demonstrates that poor sleep quality can have physiological and behavioral consequences that can negatively effect students’ health and well-being (Banks & Dinges, 2007). In 2001, Buboltz and colleagues examined sleeping patterns in a sample of 191 male and female
undergraduates. Participants completed measures that assessed their subjective sleep quality and sleep habits. Of the sample, only 11% of participants reported good sleep quality. Further, the results revealed that more than 73% of participants indicated occasional sleep difficulties, with women reporting more problems than men. These findings are consistent with previous research that found that approximately 68% of college students report experiencing sleep problems (Hicks, Johnson, & Pellegrini, 1992). Sleep difficulties endorsed by the majority of the sample included: taking more than 30 minutes to fall asleep, difficulties falling asleep more than 3 times per week, waking up too early, and morning tiredness. In fact, 54% of students surveyed reported feeling tired the next day. In another study of college students, Caldwell (2002) found that sleeping just one hour less than the recommended 8 hours per night, coupled with irregular sleep
schedules, resulted in 75% of a college student research sample reporting of feelings of fatigue. The researchers concluded that, “college students suffer a decreased level of sleep quality compared to the ‘normal’ adult population” (Buboltz et al., 2001, p. 133).
In an expanded study, Buboltz, Soper, Jenkins, Woller, Johnson, and Faes (2009) assessed sleep quality and sleep habits in a sample of 742 undergraduates. Of the sample, poor sleep quality was reported by 22% of participants, whereas 66% indicated that they experienced occasional sleep problems. Similar to the results of Buboltz et al. (2001), only 11% of participants indicated good sleep quality and 54% reported feeling “mostly tired” in the mornings. In contrast to the Buboltz et al. (2001), a higher percentage of students took more than 30 minutes to fall asleep (24% vs. 20%), experienced sleep disturbances (20% vs. 15%), experienced nocturnal awakenings (20% vs. 14%), woke up too early (18% vs. 14%), and used sleep medications (3% vs. 1%). In a sample of 313 undergraduate and graduate college students, Forquer et al. (2008) reported even higher prevalence of sleep difficulties. Of the participants, 30% reported taking longer than 30 minutes to fall asleep, 43% woke up more than once per night, and 58% reported feeling fatigued the next day. Of note, no gender differences in time to fall asleep, hours of nightly sleep, or number of awakenings were found.
In sum, empirical research suggests that college students suffer from poor sleep quality. According to Hicks, Fernandez, and Pellegrini (2001b), college students’ sleep dissatisfaction rose from 24% to 71% between 1978 and 2001. Additionally, sleep difficulties are highly prevalent among college students, particularly taking more than 30 minutes to fall asleep, difficulties falling asleep, waking up too early, and morning tiredness (Buboltz et al., 2001, 2009). Across investigations, more than half of college
students report feeling fatigued during the day (Buboltz et al., 2001, 2009; Caldwell, 2002; Forquer et al., 2008). Although findings regarding college students’ average sleep duration are mixed (Hicks et al., 2001a; Forquer et al., 2008, Hoesk et al., 2004; Liguori et al., 2011), researchers agree that college students are at high risk for sleep deprivation and poor sleep quality (Buboltz et al., 2001, 2009).
Sleep, Nutrition, and Exercise. Poor sleep quality can have significant physiological and behavioral consequences (Buboltz et al., 2001; National Sleep Foundation, 2008). Evidence has revealed cross-sectional associations between sleep deprivation and obesity. A review of the literature suggests that sleep deprivation and poor sleep quality may be related to an increased risk for obesity by de-regulating appetite, which in turn corresponds to increased energy consumption. Observational studies have detected changes in the secretory patterns of two appetite-regulating
hormones, ghrelin and leptin, as a result of insufficient sleep (e.g., Spiegel et al., 2004). Ghrelin stimulates appetite, whereas leptin decreases appetite. Together, these two opposing hormones work to control appetite and ensure that optimal energy intake and homeostasis is obtained (Valassi, Scacchi, & Cavagnini, 2008).
In 2004, Spiegel et al. examined both ghrelin and leptin levels before, during, and after induced sleep curtailment. Participants were 12 young men with healthy BMI levels who typically slept an average of 7 to 9 hours per night. The researchers obtained blood samples at 20-minute intervals after sleep was restricted to 4 hours for two consecutive nights, and after sleep was extended to 10 hours for two consecutive nights. Half of the sample received the 4 hours before the 10 hours condition, while the other half got the reverse. Participants also completed visual analogue scales for hunger and appetite. The
results revealed that leptin levels were 18% lower and ghrelin levels were 28% higher when sleep was restricted to 4 hours per night. In addition, the reciprocal changes in ghrelin and leptin in response to sleep restriction resulted in a 24% increase in hunger and a 23% increase in appetite. The greatest increase in appetite tended to be for
carbohydrate-rich foods, including sweets, salty foods, and snacks, which rose from 33-45%. In another study of 11 healthy men and women, Nedeltcheva et al. (2009) found that recurrent sleep restriction was accompanied by increased consumption of excess calories from carbohydrate-rich snacks before bedtime. Collectively, the findings suggest that sleep deprivation may have the capacity to influence nutritional choices.
Sleep deprivation leads to daytime sleepiness (Aeschbach, Postolache, Sher, Matthews, & Wehr, 2001), which may discourage participation in activities that require added physical effort or energy, such as exercise, and the preparation of nutritious meals, as opposed to purchasing food items (e.g., fast food). Thus, it is conceivable that
insufficient sleep may be a barrier to good nutrition and exercise, which can result in weight gain. Given the paucity of research in this area, Stamatakis and Brownson (2007) sought to examine the effects of sleep on nutrition and exercise behavior. The
researchers collected cross-sectional data from rural communities in Midwestern United States, obtained from a telephone-administered questionnaire that assessed common weight related behaviors, including fruit and vegetable consumption, fat intake, frequency of eating fast food, and physical activity. Based on habitual sleep duration values, participants were grouped into three categories: short sleep duration (< 7 hours), long sleep duration (≥ 9 hours), and a reference group (7-9 hours). The results revealed that short sleep duration was associated with higher levels of fast food and high-fat food
consumption along with lower levels of fruit and vegetable intake and physical activity. A subsequent experimental study by Schmid and colleagues (2009) confirmed that acute sleep loss decreases physical activity engagement in young healthy men. The researchers also observed that not only was the frequency of physical activity decreased, but the intensity of exercise was reduced to lower levels as well.
In a recent study, Bromley et al. (2012) sought to test the hypothesis that sleep curtailment would result in reduced amount and intensity of physical activity in adults at risk for type 2 diabetes. A sample of 18 young healthy men and women with a parental history for type 2 diabetes were subjected to two 7-day inpatient sessions where sleep was restricted to 5.5 or 8.5 hours. Participants who exercised regularly (39%) were allowed to follow their typical exercise regimen during both sessions. To simulate occupational activities, participants performed office-like tasks for 6 hours a day,
including working on computer, making phone calls, entering data, researching, reading, and writing. Participants spent the remainder of their waking hours engaged in leisure activities, such as watching TV, playing video games, reading, surfing the internet, or making phone calls. Continuous wrist actigraphy and waist accelerometry were used to monitor participants’ sleep and physical activity. It was found that sleep restriction was associated with 31% lower daily movement, a 24% reduction in moderate to vigorous physical activity, and more sedentary behavior. In fact, decreases in daily activity were most prominent in participants who exercised regularly (-39% vs. -4% in exercisers vs. non-exercisers, respectively). The results are consistent with the findings of Schmid et al., (2009) and St-Onge, Roberts, Chen, Kelleman, O’Keeffe, and RoyChoundry (2011) who observed a similar decrease in physical activity intensity in response to experimental
sleep curtailment. Given the established behavioral health consequences of insufficient sleep, the present study examined the influence of sleep quality in the relationships among mindfulness and nutrition and exercise behavior.
Mindfulness Definition of Mindfulness
The term “mindfulness” is complex and multifaceted, as it has been used to describe a mode of processing information, a state of awareness, a meditative practice, and a psychological trait (Brown et al., 2007). In contemporary Western psychology, researchers have attempted to develop an operational definition of mindfulness, and identify the core dimensions of the construct. One of the most commonly cited definitions of mindfulness is the awareness that arises through “paying attention in a particular way: on purpose, in the present moment, and nonjudgmentally” (Kabat-Zinn, 1994, p. 4). In a later article, Kabat-Zinn (2003) added that mindfulness includes “an affectionate, compassionate quality with the attending, a sense of openhearted, friendly presence and interest” (p. 145). Definitions and descriptions of mindfulness provided by other researchers have been similar. For example, Brown and Ryan (2003) defined mindfulness as “the state of being attentive to and aware off what is taking place in the present” (p. 822). Baer (2003) elaborated that mindfulness involves “the nonjudgmental observation of the ongoing stream of internal and external stimuli as they arise” (p. 125). Similarly, Bishop et al. (2004) defined mindfulness as the “non-elaborative awareness to current experience” with an orientation of “curiosity, experiential openness, and
acceptance” (p. 234). Although the definitions vary in regards to what facets of mindfulness they include, all seem to capture the basic elements that mindfulness
teachers have deemed important (Baer, 2011).
Brown and Ryan (2003) suggested that individuals differ in their propensity to be aware and sustain attention to the present moment. Thus, in addition to being a state of consciousness, research has demonstrated that mindfulness is a characterological trait (Brown & Ryan, 2003; Thompson & Waltz, 2007). For the purpose of the current investigation, mindfulness was treated as a “dispositional or trait-like variable that is roughly consistent over time and across situations” (Baer, 2011; p. 246). However, it is important to clarify that the inherent tendency to respond mindfully to daily activities can be enhanced with training (Baer, 2011; Brown & Ryan, 2003; Carmody & Baer, 2008). In fact, mindfulness-based treatment interventions have been shown to improve mean scores on measures of dispositional mindfulness, therefore demonstrating that
mindfulness is amenable to change with practice (Carmody & Baer, 2008; Carmody, Reed, Kristeller, & Merriam, 2008; Chambers, Lo, & Allen, 2008).
Theory of Mindfulness
While some researchers focus solely on the attentional facets of mindfulness, most have adopted Bishop and colleagues (2004) two-component model of mindfulness. The first component involves the self-regulation of attention and awareness, and the second includes the adoption of a curious, open, and accepting attitude (Bishop et al., 2004). Bishop and colleagues’ (2004) model identifies these components in terms of “specific behaviors, experiential manifestations, and implicated psychological processes” (p. 230).
Attention and awareness. According to Brown and Ryan (2004), awareness is the “subjective experience of internal and external phenomena,” whereas attention is the
“focusing of awareness to highlight selected aspects of that reality” (p. 242-243). For example, when eating, one can be highly attentive to the taste experience, while
sensitively aware of the enhanced feeling of fullness in one’s stomach (Brown & Ryan, 2003). As Bishop et al. (2004) emphasized, mindfulness specifically concerns the self-regulation of attention to the conscious awareness of one’s immediate experiences (e.g., physical sensations, perceptions, thoughts, feelings, and imagery). Further, this “self-regulation” not only involves the ability to attend to a given entity for an extended period of time, but the capacity to intentionally shift attention between objects and
simultaneously inhibit elaborative processing (Bishop et al., 2004). Thus, present moment awareness (i.e., mindfulness) enhances the direct experience of events, as opposed to the meaning prescribed to events (Shapiro, Carlson, Astin, & Freedman, 2006).
Acceptance. The second component of Bishop et al.’s (2004) model of mindfulness is acceptance. In the context of mindfulness, however, it is important to clarify that acceptance does not imply passivity or resignation (Cardaciotto, Herbert, Froman, Moitra, & Farrow, 2008), but involves the adoption of a nonjudgmental attitude that allows one to experience more fully, without distortion or bias. For example, when having a food craving, acceptance requires a nonevaluative orientation toward the craving and requires a willingness to withstand the uncomfortable, and potentially negative feelings that accompany the craving (Alberts et al., 2010). Therefore, mindfulness encourages an open and receptive attitude, and discards “one’s agenda to have a different experience” (p. 233, Bishop et al., 2004).
To date, the majority of mindfulness research has focused on the effectiveness of mindfulness-based interventions, whereas the examination of mindfulness as a
dispositional variable has been addressed by only a handful of studies in the health behavior literature. In a sample of 553 male and female college students, Roberts and Danoff-Burg (2010) investigated the relationships between mindfulness and health behaviors, in addition to the role of stress in mediating these effects. Participants completed assessments of mindfulness, perceived health, health behaviors (i.e., sleep, smoking, binge eating, physical exercise, and risky sexual activity), health-related activity restriction (e.g., missing work or school), and stress. The results revealed that participants who were more mindful engaged in less binge eating, were more physically active, and reported better sleep quality. Furthermore, stress was shown to partially mediate these relations, suggesting that greater mindfulness is related to decreased stress levels, which in turn promotes positive health behavior. Baer et al. (2006) highlighted that relaxation, defined as the reduction of tension, is one of the primary mechanisms underlying mindfulness. Stress has also been found to be significantly associated with diet (Cartwright, Wardle, Steggles, Simon, & Croker, 2003; Grunberg & Straub, 1992), physical exercise (Salmon, 2001), and sleep quality (Akerstedt, 2006; Akerstedt, Kecklund, & Axelsson, 2007). Given the aforementioned established relationships and the high prevalence of stress on college campuses (Misra & Castillo, 2004), stress was considered as a covariate in the current investigation.
In a similar investigation, Grinnell et al. (2011) sought to determine whether mindfulness is associated with anthropometric and self-report measures of diet and physical activity among 75 first-year college students. Although mindful and less
mindful participants were similar in regards to anthropometric assessments (e.g., weight, height, BMI, waist circumference, and blood pressure), differences emerged on the behavioral measures. More specifically, college students who were more mindful had a lower susceptibility to emotional eating, eating in response to external rather than internal cues, and reported less barriers to physical activity. These findings support the utility of dispositional mindfulness in promoting positive health behavior in college students.
To date, only one study has examined the unique influence of each of the five facets of dispositional mindfulness (observing, describing, acting with awareness, nonreactivity to inner experience, and nonjudging of inner experience) on college students’ nutrition and exercise behavior. In a sample of 269 male and female undergraduates, Gilbert and Waltz (2010) examined the degree to which mindfulness predicts diet, physical activity, and self-efficacy. The results revealed that college students who were more mindful reported higher levels fruit and vegetable intake, lower levels of fat intake (men only), higher levels of moderate- and vigorous-intensity physical activity, and greater self-efficacy. Interesting gender differences emerged, as the ability to observe sensation, perceptions, thoughts, and feelings predicted healthier behaviors for males, whereas the capacity to describe and apply meaning to experiences predicted healthier behaviors for females. In regards to physical activity, the observe subscale alone predicted men’s moderate and vigorous physical activity. For females, the describe subscale was predictive of moderate physical activity and the act with awareness subscale was predictive of vigorous physical activity. Concerning dietary behavior, the observe and act with awareness subscales were predictive of men’s fruit and vegetable intake. The nonreact subscale alone predicted men’s fat intake. For females, the observe
subscale alone was predictive of fruit and vegetable intake. Of note, mindfulness was not significantly associated with fat intake for women. Overall, the findings suggest that the various facets of mindfulness may be related to specific health behaviors.
In a recent longitudinal investigation, Murphy et al. (2012) examined the extent to which mindfulness predicted health behaviors (i.e., sleep, eating, and exercise) and physical health among a sample of 441 college women. Participants responded to
questionnaires that assessed mindfulness, healthy eating habits, exercise frequency, sleep quality, and physical health. Consistent with Roberts and Danoff-Burg’s (2010) findings, higher levels of mindfulness were found to be significantly related to healthy eating habits and better sleep quality. However, frequency of exercise was not significantly related to mindfulness, which the researchers attributed to methodological limitations of the scale. Given the inconsistent findings, the relationship between mindfulness and exercise behavior in college students warrants further investigation.
The examination of mindfulness and health behaviors among college students seems particularly relevant to counseling psychologists who work with college students, as the present study provides useful information for enhancing understanding of how mindfulness influences weight-related behaviors in this population. In accordance with the goal of the American Psychological Association’s Strategic Plan (APA, 2011) to expand psychology’s role in advancing health, psychologists must work to increase support, research, training, education, and interventions that improve and reduce the obesity epidemic. As experts in understanding and changing behavior, psychologists have the capacity to address some of the behavioral and environmental causes of obesity. Accordingly, the current investigation can assist in the development of
mindfulness-based interventions that may help to reduce the barriers that college students face in their effort to embrace a healthier lifestyle. Perhaps, mindfulness may be a unique and cost-effective tool for improving physical health.
Rationale and Purpose
Obesity is a complex disorder that originates from both genetic and environmental factors and may put individuals at risk for premature mortality and morbidity (Brancati et al., 2000; Mokdad et al., 2001). The epidemic proportions of overweight and obesity in the United States demonstrate that many Americans are in calorie imbalance – that is, they consume more calories than they expend. Given that people cannot control the calories they expend via metabolic processes, it is important that they decrease the amount of calories they consume from food and beverage intake, and increase caloric expenditure through exercise. Despite the established risks, nutrition and exercise represent behaviors that are often neglected by college students. Given that students begin to adopt their own health behavior patterns, college life may set the stage for establishing long-term health behavior (Dinger & Waigandt, 1997). Thus, it is
imperative that mindfulness be examined as a potentially critical factor in increasing our understanding of health behaviors among undergraduate college students.
To date, only a relatively small number of studies have addressed the utility of mindfulness in the domain of nutrition and exercise behavior among college students. Furthermore, only one study has examined the unique associations among the five facets of mindfulness and college student health behavior (Gilbert & Waltz, 2010). However, the results are promising and indicate a positive association among mindfulness and nutrition behavior (Gilbert & Waltz, 2010; Murphy et al., 2012; Roberts & Danoff-Burg,
2010). In regards to exercise behavior, the findings have been mixed (Murphy et al., 2012), but the majority of studies indicate that higher levels of mindfulness correspond to greater physical activity engagement (Gilbert & Waltz, 2010; Grinnell et al., 2011; Roberts & Danoff-Burg, 2010). Given the high prevalence of sleep deprivation and poor sleep quality among college students (Buboltz et al., 2001; Forquer et al., 2008; Hicks et al., 2001a), one may speculate whether insufficient sleep may serve as a barrier to healthy nutrition and exercise. That is, feeling fatigued may hinder one’s participation in
activities that require added physical effort, such as exercise, and healthy meal preparation. Accordingly, experimental evidence has found sleep deprivation to be associated with increased hunger and appetite for carbohydrate-rich foods (Nedeltcheva et al., 2009; Spiegel et al., 2004), and decreases in amount and intensity of physical activity (Bromley et al., 2012; Schmid et al., 2009).
In an attempt to expand on both the study of mindfulness and that of health behavior, the aim of the present study was four-fold: (a) examine the influence of sleep quality on the relationship between mindfulness and nutrition behavior; and (b) examine the influence of sleep quality on the relationship between mindfulness and exercise behavior; (c) determine which facets of mindfulness (observing, describing, acting with awareness, nonreactivity to inner experience, and nonjudging of inner experience) are most predictive of college students’ nutrition; and (d) determine which facets of mindfulness are most predictive of college students’ exercise behaviors.
Hypotheses and Research Questions
The following hypotheses and research questions were offered to address the study’s purpose:
Hypotheses
1. Sleep quality will moderate the relationship between mindfulness (total score) and nutrition behavior in undergraduate college students, such that the
interaction of mindfulness and sleep quality will explain the variance in nutrition behavior above and beyond what is explained by mindfulness and sleep quality.
2. Sleep quality will moderate the relationship between mindfulness (total score) and exercise behavior in undergraduate college students, such that the
interaction of mindfulness and sleep quality will explain the variance in exercise behavior above and beyond what is explained by mindfulness and sleep quality.
Research Questions
1. Which facets of mindfulness are most predictive of undergraduate college students’ nutrition behavior?
2. Which facets of mindfulness are most predictive of undergraduate college students’ exercise behavior?
Models of the hypotheses and research questions are presented in Figures 1 through 4.
Figure 1. Model of Hypothesis 1.
Figure 2. Model of Hypothesis 2.
Mindfulness Exercise Behavior Sleep Quality Mindfulness Nutrition Behavior Sleep Quality
Figure 3. Model of Research Question 1.
Figure 4. Model of Research Question 2. Describe Act with Awareness Nonreact Nonjudge Exercise Behavior Observe Describe Act with Awareness Nonreact Nonjudge Nutrition Behavior Observe
CHAPTER 3 METHODOLOGY
Participants
Non-probability sampling (i.e., convenience sampling) was employed in the present study. Participants included undergraduate students who were enrolled in colleges throughout the United States. Undergraduate college students were solicited for
participation for the present investigation because: (a) statistics show that being overweight and obese are highly prevalent in college student populations, and (b) research evidence demonstrates that a substantial portion of college students suffer from inadequate nutrition, physical inactivity, and poor sleep quality. When initially
determining a target sample size for this study, the recommendation by Tabachnick and Fidell (2001) was considered. These authors suggested that a sample of 8m + 50 is needed for regression analysis, where m is the number of predictors, in order to detect a medium effect size. Given that there are seven predictors in the current study, and two variables that needed to be controlled for, the target sample size for this study was, at minimum, 122 participants. However, according to Faul, Erdfelder, Buchner, and Lang (2009), a sample of up to 395 students may be needed to detect a small effect size, and achieve desired alpha level (α = .05) and power (1 - β = .80). Therefore, the present study sought a participant sample of 395 male and female undergraduates.
A total of 438 participants were recruited for this study. Sixty participants, however, were dropped form the study because although they agreed to participate, they did not respond to any survey items. Listwise deletion was used to remove an additional 2 participants from the study who completed less than half of the survey items before
discontinuing their participation. This sample was further reduced to 357 male and female undergraduates due to non-undergraduate academic status (i.e., graduate students or dual enrollment high school students, n = 10), gender identity other than male or female (i.e., transgender, n = 4), unmet age requirement (i.e., under age 18, n = 4), and a univariate outlier (n =1). The remaining sample included 164 male (45.9%) and 193 female (54.1%) undergraduates whose ages ranged from 18 to 35 years (M = 20.99, SD = 3.11). Racial/ethnic composition was as follows: 35.3% Caucasian, 30.8%
Latino/Hispanic, 18.5% Black/African American, 7.8% Asian/Asian American, 6.4% Bicultural/Multicultural, 0.6% Native American, 0.6% identified their racial/ethnic background as “other.” In regards to sexual orientation, 89.1% of participants identified heterosexual, 2.3% as gay, 1.4% as lesbian, 3.9% as bisexual, 1.1% identified their sexual orientation as “other,” and 2.2% of participants did not respond to this item. Of the participants, 24.9% were first year college students, 18.5% were sophomores, 21.3% were juniors, 27.2% were seniors, and 8.1% were fifth year seniors.
In regards to body metrics, participants’ height ranged from 58 to 77 inches (M = 67.33, SD = 4.18), with men (M = 70.36, SD = 3.07) reporting greater height than women (M = 64.76, SD = 3.15). Participants weight ranged from 95 to 320 pounds (M = 155.72, SD = 36.46), with men (M = 171.91, SD = 33.31) weighing significantly more than women (M = 141.96, SD = 33.30). Self-reported height and weight were used to calculate participants’ BMI (BMI = weight in kilograms divided by height in meters squared), which ranged from 14.23 to 41.00 kg/m2 (M = 24.04, SD = 4.71). No gender differences were observed. Adult BMI criteria were applied to describe participants as not overweight (BMI < 25.0 kg/m2), overweight (BMI = 25.0 – 29.9 kg/m2), or obese
(BMI ≥ 30.0 kg/m2). Accordingly, 70.3% of the total sample was classified as not overweight (n = 251), 19.0% as overweight (n = 68), and 10.7% as obese (n = 38). With respect to sleeping habits, participants reported sleeping an average of 3 to 12 hours per night (M = 6.78, SD = 1.23). No gender differences in habitual sleep duration were observed. Demographic information is provided in Table 1.
Table 1
Summary of Demographic Characteristics for the Total Sample
Characteristics N (%) Min Max M SD
Age 357 18 35 20.99 3.11 Height (in) 357 58 77 67.33 4.18 Weight (lbs) 357 95 320 155.72 3.15 BMI (kg/m2) 357 14.23 41.00 24.04 4.71 Not Overweight 251 (70.3%) Overweight 68 (19.0%) Obese 38 (10.7%)
Habitual sleep (hours) 357 3 12 6.78 1.23
Gender Male 164 (45.9%) Female 193 (54.1%) Race/Ethnicity Caucasian 126 (35.3%) Latino/Hispanic 110 (30.8%) Black/African American 66 (18.5%) Asian/Asian American 28 (7.8%) Bicultural/Multicultural 23 (6.4%) Native American 2 (0.6%) Other 2 (0.6%) Sexual Orientation Heterosexual 318 (89.1%) Gay 8 (2.3%) Lesbian 5 (1.4%) Bisexual 14 (3.9%) Other 4 (1.1%) Missing 8 (2.2%) (table continues)
Characteristics N (%) Min Max M Year in School First Year 89 (24.9%) Sophomore 66 (18.5%) Junior 76 (21.3%) Senior 97 (27.2%)
Fifth Year Senior 29 (8.1%) Mother’s Education Level
Some School 36 (10.1%)
High School Graduate/GED 102 (28.6%) Vocational/Technical School 17 (4.8%) 2 Year College 53 (14.8%) 4 Year College 76 (21.3%) Graduate/Professional Degree 70 (19.6%) Missing 3 (0.8%) Parental/Household Income $25,000 or less 58 (16.3%) $25,000 to $50,000 86 (24.1%) $50,000 to $75,000 72 (20.2%) $75,000 to $100,000 63 (17.6%) $100,000 or more 73 (20.4%) Missing 5 (1.4%) Measures
Measurements that were used to assess mindfulness, nutrition behavior, exercise behavior, sleep quality, perceived stress, as well as a demographic questionnaire, are described in this section (also see Appendices A through F).
Mindfulness
Mindfulness was measured using the Five-Facet Mindfulness Questionnaire (FFMQ; Baer et al., 2006), a 39-item self-report inventory that assesses five facets related to mindfulness: (1) observing or attending to sensations, perceptions, thoughts, and feelings; (2) describing or labeling experiences with words; (3) acting with awareness as
opposed to on “automatic pilot”; (4) nonreactivity or allowing thoughts and feelings to come and go, without elaboration; and (5) nonjudging or adopting a nonevaluative orientation toward inner experiences(See Appendix A). This instrument was derived from a factor analysis of questionnaires measuring the general tendency to be mindful in daily activities. The FFMQ can be scored wholly or divided into five facets: observe (8 items; e.g., “I notice the smells and aromas of things.”), describe (8 items; e.g., “I’m good at finding words to describe my feelings.”), act with awareness (8 items; e.g., “When I do things, my mind wanders off and I’m easily distracted.”), nonreact (7 items; e.g., “In difficult situations, I can pause without immediately reacting.”), and nonjudge (8 items; “I disapprove of myself when I have irrational ideas.”). For the purposes of the present investigation, all five facets were used. Participants rated their agreement with each item on a 5-point Likert-type scale, ranging from 1 (never or very rarely true) to 5 (very often or always true). Total scores range from 39 to 195, with higher scores indicating greater levels of dispositional mindfulness.
Empirical studies have used the FFMQ total scores to assess dispositional
mindfulness as an overarching mindfulness construct (e.g., Caldwell, Emery, Harrison, & Greeson, 2011), while subscale scores have been used to better understand the specific skills that are enhanced through the practice of mindfulness (e.g., Carmody, Baer, Lykins, & Olendzki, 2009). Intercorrelations of the facets range from .32 to .56, implying that the facets represent related, yet distinct constructs (Baer, Smith, Lykins, Button, Krietemeyer, & Sauer et al., 2008). Baer and colleagues (2008) conducted a
confirmatory factor analysis that supported a hierarchical model in which the five factors are indicators of an overarching mindfulness construct. Therefore, FFMQ total scores
and subscale scores were used in the main analyses.
Baer and colleagues (2006) established construct validity by examining the relationships between the mindfulness facets and other constructs. The observe facet was highly correlated to openness (.42). The describe facet was positively associated with emotional intelligence (.60) and negatively related to alexithymia (-.68). The act with awareness facet was strongly correlated with absent-mindedness .61) and dissociation (-.62). The nonreact facet was positively related with self-compassion (.53). The nonjudge facet was negatively related with thought suppression (-.56), neuroticism (-.55),
difficulties in emotional regulation (-.52), psychological symptoms (-.50), and experiential avoidance (-.49). Further, empirical studies have observed increases in FFMQ scores with the participation of the Mindfulness-based Stress Reduction group intervention (Carmody & Baer, 2008). Baer and colleagues (2006) reported adequate to good internal consistency reliability for each of the five facets of the FFMQ, with alpha values ranging from .75 (nonreact) to .91 (describe). The FFMQ demonstrated good internal consistency reliability in the current sample for the entire scale (α = .87), and adequate to good internal consistency reliability for the observe (α = .75), describe (α = .86), act with awareness (α = .83), nonreact (α = .87), and nonjudge (α = .77) subscales. Nutrition and Exercise Behavior
The Health-Promoting Lifestyles Profile-II (HPLP-II; Walker, Sechrist, & Pender 1995) is a 52-item questionnaire that can be scored wholly or divided into six subscales: health responsibility, interpersonal relations, nutrition, physical activity, spiritual growth, and stress management. Nutrition behavior was measured using the 9-item nutrition subscale of the HPLP-II, which assesses participants’ selection and consumption of
